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Enregistrement W2771856202 · doi:10.2196/jmir.8877

Development and Usability Evaluation of an Art and Narrative-Based Knowledge Translation Tool for Parents With a Child With Pediatric Chronic Pain: Multi-Method Study

2017· article· en· W2771856202 sur OpenAlexafffund
Kathy Reid, Lisa Hartling, Samina Ali, Anne Le, Allison Norris, Shannon D. Scott

Notice bibliographique

RevueJournal of Medical Internet Research · 2017
Typearticle
Langueen
DomaineHealth Professions
ThématiqueHealth Literacy and Information Accessibility
Établissements canadiensStollery Children's HospitalWomen and Children’s Health Research InstituteUniversity of AlbertaAlberta Health Services
Organismes subventionnairesChildren's Hospital FoundationStollery Children’s Hospital FoundationWomen and Children's Health Research InstituteChildren's Health Research Institute
Mots-clésUsabilityNarrativeChronic painKnowledge translationQualitative researchPsychologyMedicineMedical educationComputer scienceKnowledge managementPsychiatrySociology

Résumé

récupéré en direct d'OpenAlex

Background: Chronic pain in childhood is increasingly being recognized as a significant clinical problem for children and their families. Previous research has identified that families want information about the causes of their child’s chronic pain, treatment options, and effective strategies to help their child cope with the pain. Unfortunately, parents have reported that finding this information can be challenging. Objective: The aim of this study was to actively work together with children attending a pediatric chronic pain clinic and their parents to develop, refine, and evaluate the usability of an art and narrative-based electronic book (e-book) for pediatric chronic pain. Methods: A multiphase, multi-method research design employing patient engagement techniques was used to develop, refine, and evaluate the usability of an art and narrative based e-book for pediatric chronic pain management to facilitate knowledge translation for parents with a child with chronic pain. The multiple phases included the following: (1) qualitative interviews to compile parents’ narratives using qualitative interviews; (2) qualitative data analysis; (3) development of an e-book prototype; (4) expert clinician feedback; (5) parent usability evaluation, knowledge change, and confidence in knowledge responses using an electronic survey; (6) e-book refinement; and (7) dissemination of the e-book. Results: A 48-page e-book was developed to characterize the experiences of a family living with a child with chronic pain. The e-book was a composite narrative of the parent interviews and encompassed descriptions of the effects the condition has on each member of the family. This was merged with the best available research evidence on the day-to-day management of pediatric chronic pain. The e-book was vetted for clinical accuracy by expert pediatric pain clinicians. All parents that participated in the usability evaluation (N=14) agreed or strongly agreed the content of the e-book was easy to understand and stated that they would recommend the e-book to other families who have children with chronic pain. Our research identified up to a 21.4% increase in knowledge after using the e-book, and paired t tests demonstrated a statistically significant difference in confidence in answering two of the five knowledge questions (chronic pain is a disease involving changes in the nervous system; the use of ibuprofen is usually effective at controlling chronic pain); t13=0.165, P=.001 and t13=0.336, P=.002, respectively, after being exposed to the e-book. Conclusions: Our results demonstrate that parents positively rated an e-book developed for parents with a child with chronic pain. Our results also identify that overall, parents’ knowledge increased after using the e-book, and confidence in their knowledge about chronic pain and its management increased in two aspects after e-book exposure. These results suggest that art and narrative-based knowledge translation interventions may be useful in transferring complex health information to parents.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,089
score de la tête « metaresearch » (Gemma)0,007
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,337
Score d'incertitude au seuil0,938

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0890,007
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,339
Tête enseignante GPT0,613
Écart entre enseignants0,274 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations45
Publié2017
Routes d'admission2
Résumé présentoui

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